Rio+20: Indigenous Knowledge and Intellectual Property in Coastal and Ocean Law
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This report explores the extent to which indigenous knowledge have been advanced by the 1992 Rio Earth Summit up to Rio 20 in the evolution of coastal, ocean and marine environmental law. Parties to the Rio Earth Summit have failed to follow through on their commitments, but the state of the global environment would have been worse off without the Rio initiatives. But Indigenous knowledge issues have yet to gain traction in areas of marine genetic resources (MGR) and marine scientific research (MSR). Integrated, multidisciplinary and cross-sectoral ecosystem-based environmental management requires that Indigenous knowledge be re-engaged and not subjugated in a hierarchy of knowledge. Indigenous peoples' lifestyles and knowledge systems stand to be dramatically changed by policies in ecosystem management. Coastal, ocean and marine environmental resource governance needs to be constructed in a way that does not allow powerful global actors to exploit the natural resources of vulnerable populations. MSR is an opportunity for considering the role of intellectual property and bioprospecting as a force for public interest scientific research, rather than the appropriation of Indigenous knowledge. The urgent need to engage Indigenous issues and knowledge is just as relevant in the coastal and oceans arena as they are in other contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it